New Learning Paradigms in Soft Computing

Learning is a key issue in the analysis and design of all kinds of intelligent systems. In recent time many new paradigms of automated (machine) learning have been proposed in the literature. Soft computing, that has proved to be an effective and efficient tool in so many areas of science and techno...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Jain, Lakhmi C. (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Kacprzyk, Janusz (http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Heidelberg : Physica-Verlag HD : Imprint: Physica, 2002.
Έκδοση:1st ed. 2002.
Σειρά:Studies in Fuzziness and Soft Computing, 84
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Περιγραφή
Περίληψη:Learning is a key issue in the analysis and design of all kinds of intelligent systems. In recent time many new paradigms of automated (machine) learning have been proposed in the literature. Soft computing, that has proved to be an effective and efficient tool in so many areas of science and technology, seems to offer new qualities in the realm of machine learning too. The purpose of this volume is to present some new learning paradigms that have been triggered, or at least strongly influenced by soft computing tools and techniques, mainly related to neural networks, fuzzy logic, rough sets, and evolutionary computations.
Φυσική περιγραφή:XII, 464 p. online resource.
ISBN:9783790818031
ISSN:1434-9922 ;
DOI:10.1007/978-3-7908-1803-1